Sampling in quantitative research

1.

Chapter 12
Sampling in Quantitative
Research
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2. Question

Tell whether the following statement is true or false:
The aggregate of cases in which a researcher is
interested is called a sample.
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3. Answer

False
The aggregate of cases in which a researcher is
interested is called a population. A sample is
selection of a portion of the population to represent
the entire population.
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4. Basic Sampling Concepts in Quantitative Studies

Population: the aggregate of cases in which a
researcher is interested
Sampling: selection of a portion of the population (a
sample) to represent the entire population
Element: basic population unit about which
information is collected
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5. Eligibility Criteria

• Establish population characteristics
• Determine participation in study
• Maximize construct validity
• Inclusion
• Exclusion
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6. Question

Tell whether the following statement is true or false:
Researchers usually sample from the target
population.
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7. Answer

False
Researchers usually sample from the accessible
population but should identify the target population
to which they want to generalize their results.
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8. Basic Sampling Concepts in Quantitative Studies

Representative sample
A sample whose key characteristics closely
approximate those of the population
Sampling bias
The systematic over- or underrepresentation of
segments of the population on key variables
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9. Question

Tell whether the following statement is true or false:
Probability sampling involves random selection of
elements.
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10. Answer

True
Probability sampling involves random selection of
elements.
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11. Basic Sampling Concepts in Quantitative Studies (cont.)

Probability sampling
Involves random selection of elements
Nonprobability sampling
Does not involve selection of elements at random
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12. Nonprobability Sampling

• Convenience sampling
• Snowball sampling
• Quota sampling
• Consecutive sampling
• Purposive sampling
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13. Probability Sampling

• Simple random sampling
• Stratified random sampling
• Multistage sampling
• Cluster sampling
• Systematic sampling
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14. Power Analysis

• Estimate sample size
• Large samples preferred to small samples
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